Available in Ubuntu and Linux, the AMIs provide fully configured development environments to quickly build artificial intelligence (AI) applications using popular deep learning frameworks including TensorFlow, Apache MXNet and Gluon, PyTorch, Chainer, Microsoft Cognitive Toolkit, Caffe, Caffe2, Theano, and Keras, and are optimized for high performance on Amazon EC2 instances. For developers who want a clean slate to set up custom builds of deep learning engines, the Base AMIs are also available in Ubuntu and Linux. To speed model training, the AMIs include the latest NVIDIA GPU acceleration through pre-configured CUDA and cuDNN drivers, as well as the Intel Math Kernel Library (MKL), in addition to installing popular Python packages and the Anaconda Platform.

Using the AMIs, you can train custom models, experiment with new algorithms, and learn new deep learning skills and techniques. There is no additional charge to use the AMIs—you pay only for the AWS resources needed to store and run your applications.

Many organizations use the AMIs to quickly develop AI applications. For example, Matrix Analytics uses the AMIs and TensorFlow on AWS to build and train computer vision algorithms to read patient scans for prediction and diagnosis of cancer. In addition, Zocdoc uses the AMIs and TensorFlow to develop deep learning algorithms for their mobile solution, which helps patients navigate insurance providers and matches patients and doctors more efficiently.